GE-CMU: description of the SHOGUN system used for MUC-5

ABSTRACT

This paper describes the GE-CMU TIPSTER/SHOGUN system as configured for the TIP-STER 24-month (MUC-5) benchmark, and gives details of the system's performance on the selected Japanese and English texts. The SHOGUN system is a distillation of some of the key ideas that emerged from previous benchmarks and experiments, emphasizing a simple architecture in which the focus is on detailed corpus-based knowledge. This design allowed the project to meet its goal of achieving advances in coverage and accuracy while showing consistently good performance across languages and domains.

REFERENCES

• 1: Paul S. Jacobs , Lisa F. Rau, Innovations in text interpretation, Artificial Intelligence, v.63 n.1-2, p.143-191, Oct. 1993 [doi>10.1016/0004-3702(93)90016-5]
• 2: T. Kitani and T. Mitamura. A Japanese Preprocessor for Syntactic and Semantic Parsing. In Ninth IEEE Conference on Artificial Intelligence for Applications. IEEE, 1993.
• 3: Susan W. McRoy, Using multiple knowledge sources for word sense discrimination, Computational Linguistics, v.18 n.1, p.1-30, March 1992
• 4: Fernando Pereira, Finite-state approximations of grammars, Proceedings of the workshop on Speech and Natural Language, p.20-25, June 24-27, 1990, Hidden Valley, Pennsylvania [doi>10.3115/116580.116592]
• 5: Masaru Tomita, Efficient Parsing for Natural Language: A Fast Algorithm for Practical Systems, Kluwer Academic Publishers, Norwell, MA, 1985